pengfeiDong

Computational biologist.

[Center for Disease Neurogenomics @CDNeurogenomics]

Today we're publishing nine #PsychAD papers across @NaturePortfolio journals, mapping 6.3M+ brain cells to study aging, disease, genetic regulation and new computational methods. Explore the PsychAD collection: https://t.co/ztlMTF1mkg Learn more: https://t.co/rKxEXip3Nd

[Donghoon Lee @hoondy]

Thrilled to share our new study out today in Nature Genetics: the most detailed map yet of the brain's own immune cells in aging and Alzheimer's disease — including a subtype that appears to protect the brain as the disease advances. 🧵

[Jun Cheng @s6juncheng]

Excited to share #AlphaGenome, a start of our AlphaGenome named journey to decipher the regulatory genome! The model matches or exceeds top-performing external models on 24 out of 26 variant evaluations, across a wide range of biological modalities.1/6

[Jaroslav Bendl @JaroslavBendl]

Excited to share our latest review in @TrendsGenetics
https://t.co/a680CCF6Cu

[Xi Fu @alexanderfuxi]

GET is finally published!
- Paper: https://t.co/O1jIzeA3xl (new validations, dry and wet)
- Model: https://t.co/WVS6MfKnWS (new tutorial on PBMC 10x Multiome data)
- Analysis package: https://t.co/aswdZG2FRq
- Demo: https://t.co/CYkQMtj8TU
- Docker: https://t.co/rzhO7W0A6U

[pengfeiDong @PengfeiD]

@alexanderfuxi Congrats!

[Center for Disease Neurogenomics @CDNeurogenomics]

🧠 New brain atlas reveals region-specific gene regulation & promoter-isoform insights, advancing neuropsychiatric disorder research & genetic fine-mapping. #Genomics #Neuroscience #cdneurogenomics #roussoslab

Read more in #NatureCommunications https://t.co/zRjuclDahI

[Center for Disease Neurogenomics @CDNeurogenomics]

🎉 Excited to announce preprints from the first #PsychAD package! Check out details of our work at https://t.co/BhkOaqATQV

🧵 Found out summary of papers below👇

[Center for Disease Neurogenomics @CDNeurogenomics]

The Center for Disease Neurogenomics (CDN) had a successful retreat day. The year 2024 marked the 10-year anniversary of the lab, and we have grown to 67 members. #CDN #retreat

[Donghoon Lee @hoondy]

We are thrilled to share a preprint on human myeloid cells and AD. Collaboration with @panos_roussos @FullardJohn @ChrisAPorras @collin_spencer_ @MilosPjanic @PhilippWeiler7 and many others.

[pengfeiDong @PengfeiD]

Please check out the preprint of our lab's new single-cell software, Dreamlet, a faster, memory-efficient statistical model for large-scale single-cell differential expression analysis.

[Gabriel Hoffman @g_e_hoffman]

Our new software dreamlet scales differential expression analysis for single cell data: https://t.co/wczjezkTvG Checkout the R package: https://t.co/PBDCY3T0gY

[pengfeiDong @PengfeiD]

@Bun_Without_B no problem. I think you can derive this information from https://t.co/JVxv69EU7J

[pengfeiDong @PengfeiD]

Excited to share our recent preprint with multi-regional RNAseq and ATACseq profilings to explore the differences among brain regions and better understand disease heritability. @panos_roussos @LabRoussos https://t.co/diBOvkZXsA.

[pengfeiDong @PengfeiD]

@XiaotaoWang3 Thanks!

[pengfeiDong @PengfeiD]

Thrilled to share our study in @NatureGenet on population-level analysis of transcribed enhancers. Thanks to my colleagues at @LabRoussos and reviewers for helping to improve it. https://t.co/QYmQ2Sx8m2

[pengfeiDong @PengfeiD]

@Bun_Without_B Thanks, An. The table and DEG results are available at https://t.co/JVxv69EU7J.

[pengfeiDong @PengfeiD]

@LindsayRizzardi @panos_roussos @LabRoussos Thanks for sharing the two manuscripts very interesting works!

[pengfeiDong @PengfeiD]

We found a promoter co-accessibility module that is robustly associated with the common variants of ASD, BD, and SCZ. More importantly, the enrichment is independent of reported cell type-specific gene expression and annotated schizophrenia-susceptible pathways.

[pengfeiDong @PengfeiD]

We identified an enhancer chromatin co-accessibility that exhibits a >50 times per SNP heritability than the baseline model for SCZ common risk variants, and the genes are strongly associated with different subclasses of SCZ susceptible pathways.